System for deriving electrical characteristics and non-transitory computer-readable medium

ABSTRACT

An object of the present disclosure is to provide a system for deriving a type of a defect of a semiconductor element and a non-transitory computer-readable medium. The system receives, from the image acquisition tool, image data obtained by sequentially irradiating a plurality of patterns provided on the semiconductor wafer with a beam and extracts characteristics of the plurality of patterns sequentially irradiated with a beam from the received image data, the characteristics being included in the image data, or receives characteristics of the plurality of patterns sequentially irradiated with a beam from the image acquisition tool, the characteristics being extracted from the image data (Step  603 ), and derives (Step  605 ) a type of a defect by referring to (Step  604 ) related information for the characteristics of the plurality of patterns, the related information storing the characteristics of the plurality of patterns and types of defects in association with each other.

TECHNICAL FIELD

The present disclosure relates to a system for deriving electricalcharacteristics and a non-transitory computer-readable medium, and, inparticular, relates to a system for deriving electrical characteristicsfrom characteristics obtained from image data and a non-transitorycomputer-readable medium.

BACKGROUND ART

When an image is formed using an electron microscope, a pattern isirradiated with a beam to charge the pattern, and a difference inbrightness between the charged pattern and other portions is clarifiedsuch that the specific pattern in the image can be highlighted. Thisimage is called a voltage contrast (VC) image. PTL 1 discloses a methodof estimating electrical characteristics of a defect portion using acorrespondence between a voltage contrast image and electricalcharacteristics of the defect portion. In particular, PTL 1 describesthat a netlist including information regarding electricalcharacteristics of a circuit element and a connection relationship isgenerated based on layout data of a sample.

CITATION LIST Patent Literature

-   PTL 1: Japanese Patent No. 4891036

SUMMARY OF INVENTION Technical Problem

In the method disclosed in PTL 1, an influence of an interaction betweena plurality of devices through a device on a lower layer on a VC imageis not considered. Therefore, when a main factor of the voltage contrastis the interaction between a plurality of devices, electricalcharacteristics of a defect portion cannot be estimated, and the type ofa defect of an element cannot be derived. Hereinafter, a system thatderives electrical characteristics in order to derive the type of adefect of an element formed on a sample based on voltage contrastacquisition, and a non-transitory computer-readable medium will bedescribed.

Solution to Problem

According to one aspect for achieving the object, there is provided asystem that detects a defect of an electric circuit formed on asemiconductor wafer from image data acquired from an image acquisitiontool or characteristics extracted from the image data. The systemreceives, from the image acquisition tool, image data obtained bysequentially irradiating a plurality of patterns provided on thesemiconductor wafer with a beam and extracts characteristics of theplurality of patterns sequentially irradiated with a beam from thereceived image data, the characteristics being included in the imagedata, or receives characteristics of the plurality of patternssequentially irradiated with a beam from the image acquisition tool, thecharacteristics being extracted from the image data, and derives a typeof a defect by referring to related information for the characteristicsof the plurality of patterns, the related information storing thecharacteristics of the plurality of patterns and types of defects inassociation with each other.

Advantageous Effects of Invention

With this configuration, a type of a defect of an element formed on asample can be specified.

BRIEF DESCRIPTION OF DRAWINGS

FIGS. 1A and 1B show an electron microscope image of a pattern formed ona semiconductor wafer and a cross-section of the electron microscopeimage.

FIG. 2 is a diagram showing an example of a system including a scanningelectron microscope.

FIG. 3 is a diagram showing an example of an electrical characteristicderivation system.

FIG. 4 is a flowchart showing an inspection recipe generation process.

FIG. 5 is a diagram showing an example of an inspection recipe settingscreen.

FIG. 6 is a flowchart showing an inspection process using the inspectionrecipe.

FIG. 7 is a diagram showing another example of the electricalcharacteristic derivation system.

FIG. 8 is a flowchart showing a process of outputting defect informationbased on a comparison between characteristics that are obtained based onbeam scanning on a plurality of patterns and characteristics of aplurality of patterns that are derived from a netlist.

FIG. 9 is a diagram showing an example of a GUI screen through which thesetting of an inspection condition and the display of an inspectionresult are executed.

FIG. 10 is a diagram showing an example of a GUI screen on which anelectron microscope image and an estimated image derived from a netlistare displayed as an inspection result

FIG. 11 is a flowchart showing a process of specifying defectinformation from brightness information obtained when a plurality ofpatterns are irradiated with a beam under a plurality of beamirradiation conditions.

FIG. 12 is a diagram showing an example of a GUI screen on which achange in characteristics of a pattern depending on a change in beamcondition is displayed.

FIG. 13 is a diagram showing an example of an electrical characteristicderivation system in which a netlist group including a plurality ofnetlists is prepared in units of manufacturing processes of asemiconductor.

FIG. 14 is a diagram showing an example of a GUI screen through which anetlist group can be selected depending on different processes.

FIG. 15 is a diagram showing an example of a system for estimating anabnormal process among semiconductor manufacturing processes.

FIG. 16 is a diagram showing still another example of the electricalcharacteristic derivation system.

FIG. 17 is a diagram showing a configuration of a DRAM.

FIG. 18 is a flowchart showing a DRAM reliability evaluation process.

FIG. 19 is a diagram showing an example of a GUI screen through which areliability determination result of a semiconductor element is displayedas an inspection result.

FIGS. 20A and 20B show an electron microscope image in which a pluralityof plugs including a defect are displayed and a cross-section of theelectron microscope image.

FIG. 21 is a diagram showing an example of a system for classifying atype of a defect.

FIG. 22 is a diagram showing an example of a scanning trajectory when aplurality of patterns are scanned with a beam in a plurality ofdirections.

DESCRIPTION OF EMBODIMENTS

(a) of FIG. 1 is a diagram showing an example of an electron microscopeimage of a pattern formed on a semiconductor wafer. In addition, (b) ofFIG. 1 is a diagram showing an A-A cross-section of (a) of FIG. 1 . FIG.1 shows a simple structure of a transistor formed on a semiconductorwafer. Diffusion layers 102 and 103 are stacked on a well 101, and agate electrode 105 is formed over the diffusion layers 102 and 103through a gate oxide film 104. In addition, a side wall 106 is formed ona side wall of the gate electrode 105. Further, an electrode (a sourcecontact 108 (first terminal), a gate contact 109 (second terminal), anda drain contact 110 (second terminal)) in contact with each of thediffusion layer 102, the gate electrode 105, and the diffusion layer 103is formed with an interlayer oxide film 107 interposed therebetween.

When a sample is scanned with an electron beam along a scanningtrajectory 111 as shown in FIG. 1 , first, the electron beam passesthrough the source contact 108, subsequently passes through the gatecontact 109, and finally reaches the drain contact 110. In this way,respective patterns are present at different positions and thus aresequentially irradiated with a beam at different timings.

While the source contact 108 among the respective contacts as theterminals of the transistor is being irradiated with a beam, secondaryelectrons are emitted from the source contact 108. When the amount ofsecondary electrons is more than the amount of electrons to be incident,the source contact 108 is positively charged, the electrons emitted fromthe positively charged source contact 108 return to the sample side, andthe source contact 108 is darker than an energized electrode. Next, whenthe gate contact 109 is irradiated with a beam, charge is accumulated inthe gate, and thus, the gate contact 109 is also darker than anenergized electrode.

When the drain contact 110 is irradiated with a beam, the gate is openedbecause the gate contact 109 is previously irradiated with a beam andcharge is accumulated therein. The drain contact 110 is electricallyconnected to the source contact 108, and thus charge is not accumulatedtherein. As a result, the drain contact 110 is brighter than the sourcecontact 108.

In addition, when the gate electrode 105 and the gate contact 109 thatare supposed to be connected to each other are not connected (opendefect), the gate is not opened even when charge is accumulated in thegate contact 109. Therefore, the drain contact 110 is also dark as inthe source contact 108.

Since a brightness condition significantly changes depending on a beamirradiation condition, the above description is merely one example.However, when a plurality of elements (in this example, the contacts)connected to a semiconductor element are irradiated with a beam in aspecific direction or in a specific order, an image corresponding to thetype of a defect of the semiconductor element is formed.

In the embodiments described below, a system and a non-transitorycomputer-readable medium will be described. In the system, a pluralityof characteristics (brightness information, contrast information) areextracted from images acquired when beam scanning is performed such thata plurality of patterns forming a semiconductor element are sequentiallyirradiated with a beam, and a type of a defect is calculated byreferring to related information for the plurality of characteristics,the related information storing the plurality of characteristics andtypes of defects in association with each other.

Embodiment 1

FIG. 2 is a diagram showing an example of a system including a scanningelectron microscope as one aspect of an image acquisition tool thatacquires image data.

The scanning electron microscope is configured with an intermittentirradiation system, an electron optical system, a secondary electrondetection system, a stage mechanism system, an image processing system,a control system, and an operation system. The intermittent irradiationsystem is configured with an electron beam source 1 (charged particlesource) and a pulsed electron generator 4. In the present invention, thepulsed electron generator 4 is separately provided. However, an electronbeam source that can radiate a pulsed electron can also be used. Inaddition, in the present embodiment, a pulsed beam is generated by usingthe pulsed electron generator 4 as a deflector that blocks irradiationof a sample with a beam and intermittently blocking the beam using adeflector. For example, a pulsed beam may be generated by changing aposition of a movable diaphragm with high speed.

The electron optical system is configured with a condenser lens 2, adiaphragm 3, a deflector 5, an objective lens 6, and a sample electricfield controller 7. The deflector 5 is provided to one-dimensionally ortwo-dimensionally scan the sample with the electron beam and is a targetto be controlled as described below.

The secondary electron detection system is configured with a detector 8and an output adjustment circuit 9. The stage mechanism system isconfigured with a sample stage 10 and a sample 11. The control system isconfigured with an acceleration voltage controller 21, an irradiationcurrent controller 22, a pulse irradiation controller 23, a deflectioncontroller 24, a focusing controller 25, a sample electric fieldcontroller 26, a stage position controller 27, and a control transmitter28. The control transmitter 28 controls writing of a control value toeach of the controllers based on input information input from anoperation interface 41.

Here, the pulse irradiation controller 23 controls an irradiation timethat is a time for which an electron beam is continuously radiated, anirradiation distance that is a distance by which an electron beam iscontinuously radiated, a blocking time that is a time betweenirradiation and irradiation of an electron beam, or an inter-irradiationpoint distance that is a distance interval between irradiation andirradiation of an electron beam. In the present embodiment, the pulseirradiation controller 23 controls the irradiation time that is a timefor which an electron beam is continuously radiated and the blockingtime that is a time between irradiation and irradiation of an electronbeam.

The image processing system is configured with a detection signalprocessing unit 31, a detection signal analysis unit 32, an image orelectrical characteristic display unit 33, and a database 34. Thedetection signal processing unit 31 or the detection signal analysisunit 32 of the image processing system includes one or more processorsand executes an arithmetic operation of brightness of a designatedinspection pattern, an arithmetic operation of a difference inbrightness between a plurality of inspection patterns, or an arithmeticoperation of analyzing or classifying electrical characteristics basedon brightness or a difference in brightness. The database 34 of theimage processing system is a storage medium that stores calibration datawhen the arithmetic operation or the like of analyzing electricalcharacteristics is executed such that the calibration data is read andused during the arithmetic operation.

A control described below, image processing, and the like are executedby one or more computer systems including one or more processors. Theone or more computer systems are configured to execute an arithmeticmodule stored in a predetermined storage medium (computer-readablemedium) in advance, and automatically or semi-automatically execute aprocess as described below. Further, the one or more computer systemsare configured to be communicable with the image acquisition tool.

FIG. 3 is a diagram showing one example of an electrical characteristicderivation system. The system shown in FIG. 3 includes an imageacquisition tool 301 such as a scanning electron microscope, a netliststorage medium 302, and a computer system 303. A netlist stored in thenetlist storage medium 302 is data including electrical characteristicsof a circuit element forming an equivalent circuit and connectioninformation between terminals in the equivalent circuit. The presentembodiment describes an example in which a position or a region to beinspected is specified using the netlist, and when a defect is detected,information thereof is recorded in the netlist. Respective componentsforming this system are connected to each other through a bus ornetwork.

In the computer system 303, a memory 306 that stores a module(application) required for a defect inspection and one or moreprocessors 305 that execute a module or an application stored in thememory 306 are built. Further, the computer system 303 includes aninput/output device 304 that inputs information required for aninspection and outputs an inspection result or the like.

The memory 306 stores a recipe generation application 307 (also referredto as a component) that generates an operation program (inspectionrecipe) of the image acquisition tool 301 during inspection of a samplesuch as a semiconductor wafer based on an sample condition or aninspection condition input from the input/output device 304 andinformation acquired from the netlist. In addition, the memory 306stores a netlist-coordinate conversion application 308 which derivescoordinates of an element forming a semiconductor element (for example,an element such as CMOS or STT-MRAM) designated by the input device 304or coordinates a region including a terminal of the element based on acorrespondence table (database) between the semiconductor element on thenetlist and actual coordinates on a semiconductor wafer.

FIG. 4 is a flowchart showing an inspection recipe generation process.FIG. 5 is a diagram showing an example of an inspection recipe settingscreen. A GUI screen 501 is displayed on, for example, a display deviceprovided in the input/output device 304. In the GUI screen 501, adisplay field for setting a type (sample information) of a semiconductorelement (target) to be inspected and an input field for inputting adevice condition (inspection condition) of the image acquisition toolare provided. In the present embodiment, the scanning electronmicroscope is adopted as the image acquisition tool. Therefore, a fieldof “SEM condition” is provided as the inspection condition.

In the input field of the sample information, an input field 502 forinputting information of the sample (for example, a semiconductorwafer), an input field 503 for inputting the type of the semiconductorelement, an input field 504 for inputting layer information of thesemiconductor wafer, and an input field 505 for inputting the type ofthe netlist are provided. The recipe generation application 307 readsthe corresponding netlist from the netlist storage medium 302 based onthe input sample information and the input layer information (Steps 401,402, and 403).

Further, the netlist-coordinate conversion application 308 searches forthe input semiconductor element in the read netlist and specifies thecoordinates of the semiconductor element on the semiconductor wafer(Steps 404 and 405). The recipe generation application 307 generates arecipe such that the field of view (FOV) of the scanning electronmicroscope is positioned at the specified coordinates (Step 406).Specifically, a driving condition or the like of a sample stage providedin the scanning electron microscope is set such that the selectedelement is positioned immediately below an electron beam.

In addition, in the input field of the inspection condition, an inputfield 506 for setting the size of the FOV, an input field 507 forinputting an acceleration voltage of the electron beam, an input field508 for inputting a probe current of the electron beam, an input field509 for inputting the number of frames (the cumulative number ofimages), an input field 510 for setting a scan direction of a beam, aninput field 511 for setting a scan speed of a beam, and an input field512 for setting a blocking time of a pulsed beam are provided.

The recipe generation application 307 generates a recipe such that thespecified coordinates are irradiated with a beam under the inspectioncondition input to the input field of the inspection condition (Step406). More specifically, for example, an extraction electrode in thescanning electron microscope, a voltage applied to an accelerationelectrode, and a scanning signal supplied to a scanning deflector areset based on the input inspection condition.

FIG. 6 is a flowchart showing an inspection process using the recipegenerated as described above. In the scanning electron microscope,first, the sample stage on which the semiconductor wafer as the targetto be inspected is placed is operated such that a field of view positionregistered in the recipe is irradiated with a beam (Step 601). Next, bycontrolling the scanning deflector and one-dimensionally ortwo-dimensionally scanning the sample with a beam, a signal waveform orimages is acquired (Step 602). At this time, beam scanning is performedsuch that a plurality of terminals of the element to be inspected areincluded in the field of view. In addition, the beam scanning isperformed such that scanning with a beam is performed with respect tothe arrangement of patterns from a set direction, and a control deviceprovided in the scanning electron microscope controls the scanningdeflector and a blanking deflector such that scanning with a pulsed beamhaving a set scan speed and a set blocking time is performed.

In the present embodiment, the example in which beam scanning isperformed along a scanning trajectory such that the beam is radiated inan arrangement direction of the patterns according to the arrangementorder has been described. However, the present disclosure is not limitedto this example, another beam irradiation method of irradiating patternsforming one element or a terminal of the element with a beam atdifferent timings may be adopted.

Next, a characteristic extraction application 311 shown in FIG. 3extracts characteristics of a plurality of patterns from the signalwaveform or the image data (Step 603). As the characteristics,brightness of a plurality of patterns, a contrast to a referencelightness (brightness ratio), an increase rate in brightness to thenumber of times of scanning, a pattern dimension or shape, and the likecan be considered. An inspection application 310 executes defectclassification by referring to a database for a combination of aplurality of characteristics extracted from the signal waveform or theimage, the database storing a type of a defect and the combination ofthe plurality of characteristics in association with each other (Steps604 and 605).

A defect characteristic database 309 stores a plurality of differentdatabases depending on sample conditions or inspection conditions, andthe inspection application 310 selects an appropriate databasecorresponding to a sample condition or an inspection condition setduring the generation of the recipe and performs defect classificationor specifies a type of a defect by referring to the selected databasefor the extracted plurality of characteristics.

By sequentially irradiating the plurality of patterns with a beam asdescribed above, the semiconductor element is allowed to function, andthe state thereof is evaluated. As a result, whether or not a defect ispresent can be specified or defect classification can be performed.

In the present embodiment, the example of irradiating a plurality ofpatterns with a beam according to a desired order by allowing a scandirection to vary has been described. However, the present disclosure isnot limited to this example. Even when the scan direction is fixed,determination on whether or not a defect is present or defectclassification can be performed by storing how characteristics of apattern are derived due to the scan direction in the database inadvance. In the configuration in which a plurality of patterns areirradiated with a beam at different timings, the above-described defectclassification can be realized.

Embodiment 2

FIG. 7 is a diagram showing another example of the electricalcharacteristic derivation system. The system shown in FIG. 7 isdifferent from the system shown in FIG. 3 , in that a storage medium ofa normal electronic device equivalent circuit netlist (normal equivalentcircuit netlist storage medium 703), a storage medium of a defectiveelectronic device equivalent circuit netlist 1 (defective equivalentcircuit netlist 1 storage medium 704), and a storage medium of adefective electronic device equivalent circuit netlist 2 (defectiveequivalent circuit netlist 2 storage medium 705) are communicablyconnected to the computer system 303. In the defective electronic deviceequivalent circuit netlist, electrical characteristics of a circuitelement forming an equivalent circuit including a defect and connectionrelationship information are recorded. In addition, a plurality ofdefective electronic device equivalent circuit netlists can be provideddepending on types of defects. In the present embodiment, the electricalcharacteristics of the circuit element and the connection relationshipinformation recorded in the defective electronic device equivalentcircuit netlist are uniquely designated. However, a range of theelectrical characteristics of the circuit element and a range of theconnection relationship may be designated. Further, the memory 306stores a data comparison application 701 that determines a rate ofconcordance between images or between netlists and an application 702for image simulation.

The electrical characteristic derivation system derives electricalcharacteristics according to a flowchart shown in FIG. 8 . Images areacquired according to the flowchart shown in FIG. 6 , and brightnessinformation of a plurality of patterns are acquired. Next, the computersystem 303 reads the normal equivalent circuit netlist and one or moredefective equivalent circuit netlists from the storage mediums of therespective netlists. The application 702 for image simulation simulatesbrightness information of a pattern to be inspected from the defectinformation (normal information) and the inspection information includedin the netlist (Step 801).

In the defective equivalent circuit netlist, for example, a differencein electrical characteristics of a connection portion in the equivalentcircuit is described as information. The application 702 for imagesimulation executes simulation of adjusting brightness by the differencein electrical characteristics from those of the normal circuit. Inaddition, since the brightness of a pattern during beam irradiationchanges depending on inspection conditions such as a beam irradiationcondition (for example, a scan speed of a beam or a blocking time of apulsed beam), the application 702 for image simulation executessimulation of brightness of each pattern according to input of theabove-described brightness modulation factors. The shape or arrangementof patterns is determined from the layout data or the images acquired inStep 602. The brightness information of respective regions segmentedfrom the shape is estimated by simulation, and the brightnessinformation obtained by simulation is assigned to each region.

The above-described simulation is executed in units of netlists, thedata comparison application 701 compares the brightness informationobtained for each netlist to the brightness information obtained in Step603 (Step 802). The data comparison application 701 compares thebrightness information obtained for each of the plurality of netlists tothe brightness information obtained in Step 603, and selects brightnessinformation having the minimum difference or satisfying a predeterminedcondition (for example, the difference in brightness informationobtained in Step 603 is less than or equal to a predetermined value)(Step 803). The computer system 303 outputs defect information (ornormal information) in a netlist corresponding to the selectedbrightness information as an inspection result (Step 804).

As described above, the defect information is described in the defectnetlist. Therefore, a defect can be accurately specified by selectionbased on a comparison to an actual image. In addition, the output is notnecessarily a defect name such as “normal”, “defect type A”, or “defecttype B” and may be a classification with which abnormal defects can beseparated. Further, as the defect type A and the defect type B, adifference in the size of individual electrical characteristics(resistance, capacitance, semiconductor characteristics) of a portion ina netlist or whether or not a plurality of patterns are connected may beoutput.

In the above-described embodiment, the example of obtaining thebrightness information (characteristics) by simulation has beendescribed. However, when a relationship between the netlist and thebrightness information (electron microscope image) is known, defectclassification may be performed by preparing a database storing thenetlist and the electron microscope image in association with each otherand comparing an actual image and the electron microscope image storedin the database to each other.

In addition, in the present embodiment, the example of calculating thebrightness information from the netlist by simulation and comparing thecalculated brightness information to the brightness information of anactual image has been described. However, defect classification may beperformed by converting the brightness information obtained from anactual image into a netlist by simulation or the like and comparing thenetlists to each other.

FIG. 9 is a diagram showing an example of a graphical user interface(GUI) screen on which an inspection condition during defect inspection(defect classification) and the derived inspection result(classification result) are displayed. In the input field of theinspection condition, an input field for a device condition such as anoptical condition or a modulation condition, a field for selection ofdesign data (layout data) of a semiconductor device as a target, a fieldfor selection of a normal device netlist, and a field for selection of aplurality of defective device netlists for each defect type areprovided. Through the input field for a device condition such as anoptical condition or a modulation condition, the size of FOV, anacceleration voltage of an electron beam, a probe current of an electronbeam, the number of frames (the cumulative number of images), a scandirection of a beam a scan speed of a beam, an blocking time of a pulsedbeam, an irradiation time of a pulsed beam, and the like can be input.The application 702 for image simulation acquires brightness information(electron microscope image) based on the above-described input values.In addition, a classified defect distribution can be displayed on thedisplay field of the inspection result.

FIG. 10 is a diagram showing an example of a GUI screen on which anactual image (electron beam irradiation result) and an estimated image(estimated irradiation result) that is estimated by simulation aredisplayed. In the example of FIG. 10 , the rate of concordance of theimages output from the data comparison application 701 is displayed. Byperforming the above-described display, an operator can verify theclassification result.

Embodiment 3

FIG. 11 is a flowchart showing a process of estimating a defect typefrom a plurality of images acquired by performing beam scanning underdifferent beam conditions (a scan speed of a beam or a blocking time ofa pulsed beam). In the present embodiment, a plurality of images areacquired (Step 602) by setting a plurality of beam conditions (Step1101). In the present embodiment, when the gate contact 109 isirradiated with a beam under different amounts of irradiation charge,the transition of brightness of the drain contact 110 is monitored. Theamount of irradiation charge can be changed by adjusting, for example,the irradiation time or the amount of a current of a beam.

In the present embodiment, an example in which a process of irradiatingthe gate contact 109 with a beam for accumulating charge andsubsequently irradiating the drain contact 110 with a beam for formingan image is repeated will be described.

FIG. 12 is a diagram showing an example of a GUI screen for displaying agraph representing the transition of brightness of the drain contact 110depending on a change in the amount of irradiation charge of a beam withwhich the gate contact 109 is irradiated. As described above, whencharge is accumulated in the gate electrode such that the gate isopened, the source and the drain are electrically connected. In thenormal circuit, when charge is accumulated in the gate to some extent,the gate is opened and the source and the drain are electricallyconnected. Therefore, the drain contact 110 becomes brighter. In FIG. 12, No. 0 represents the transition of brightness of the normal equivalentcircuit and shows a state where, when charge is accumulated to someextent, the brightness of the drain contact becomes high.

On the other hand, No. 1 in FIG. 12 shows a state where a low brightnessstate is maintained because the source and the drain are notelectrically connected although charge is accumulated in the gate. Thisshows the possibility of an open defect in which the gate is not openedbecause the gate contact 109 and the gate electrode 105 are not incontact with each other. In addition, No. 2 in FIG. 12 shows a statewhere the gate is not opened unless a large amount of charge is appliedto the gate electrode as compared to the normal circuit. This shows astate where charge leaks from the gate electrode 109 to the well 101such that charge is not likely to be accumulated in the gate electrode109. Further, No. 3 in FIG. 12 shows a state where the brightness of thedrain contact is high irrespective of accumulation of charge in the gateelectrode. The reason for this is presumed that charge leaks from thedrain to the well such that the brightness of the drain contact is highirrespective of whether or not the gate is opened.

The above-described transition of brightness changes depending on defecttypes. Therefore, by evaluating the transition of brightness, defecttype classification can be performed. In the flowchart shown in FIG. 11, the computer system 303 generates a curve (first S curve) shown inFIG. 12 (Step 1103) and subsequently generates a plurality of curves(second S curves) from the normal equivalent circuit netlist and one ormore defective equivalent circuit netlists (Step 1104). In addition, thecomputer system 303 compares the first S curve and the second S curves(Step 1105) to each other and outputs defect information (or normalinformation) of a netlist corresponding to the second S curve having thehighest rate of concordance (Steps 1106 and 1107).

In the above-described configuration, electrical characteristics of asemiconductor element can be evaluated. FIG. 12 illustrates an exampleof calculating the rate of concordance with respect to the S curveindicating normality. However, whether or not a defect is present may bedetermined based on the rate of concordance without generating the Scurve from the defective equivalent circuit netlist. In addition, theshape of the S curve has a characteristic that varies depending ondefect types. Therefore, by acquiring shape information of the S curvescorresponding to defect types in advance, a defect type may bedetermined according to the rate of concordance of each of the S curves.

Embodiment 4

FIG. 13 is a diagram showing an example of an electrical characteristicderivation system in which a netlist group including a plurality ofnetlists is prepared in units of manufacturing processes of asemiconductor. In the system shown in FIG. 13 , by comparing brightnessinformation obtained from an actual image and brightness informationobtained from a netlist group to each other, not only a defect type butalso a manufacturing process that brings about a defect can bespecified.

For example, a storage medium 1301 of a process A abnormal equivalentcircuit netlist group stores a plurality of netlists including a poorfilm quality defect of a magnetic tunnel junction (MTJ) of STT-MRAM.When it is determined that the poor film quality defect of MTJ occursmainly due to insufficient adjustment of a manufacturing condition of aprocess A, a plurality of netlists including the corresponding defectare stored, and a brightness information group derived from the netlistsand brightness information extracted from an actual image are comparedto each other to determine whether or not the adjustment of the processA is insufficient.

More specifically, a netlist group is stored for each of the process A,a process B, and a process C, a brightness information group derivedfrom each of the groups is compared to the brightness informationderived from an actual image, and a process relating to group havingbrightness information close to the brightness information derived froman actual image is determined. As a result, a process that brings aboutthe defect is determined.

The computer system 303 performs the above-described determination, forexample, along the flowchart shown in FIG. 8 . In Step 802, thebrightness information group for each netlist group and the brightnessinformation obtained from an actual image are compared to each other. InStep 803, a group having brightness information close to the brightnessinformation obtained from an actual image or a group to which thebrightness information obtained from an actual image belongs isselected. In Step 804, a process name corresponding to the selectedgroup is output. In addition, the probability of a process depending onthe closeness to each of the groups may be output. Further, when thecorresponding process is not present, the result of the determinationmay be “Others”.

In the above-described computer system, a manufacturing process thatbrings about a defect can be specified. When a STT-MRAM is a target, itis considered that a plurality of netlists including a carrier lossdefect is stored in a storage medium 1302 of a process B abnormalequivalent circuit netlist group, and a plurality of netlists includinga gate insulating film quality defect is stored in a storage medium 1303of a process C abnormal equivalent circuit netlist group.

FIG. 14 is a diagram showing an example of a GUI screen which isdifferent from the GUI screen shown in FIG. 8 in that a netlist groupcan be selected as an inspection condition for each of differentprocesses. Netlist groups that are managed in units of processes can beselected, and characteristics derived from the netlist groups andcharacteristics derived from an actual image can be compared to eachother. As a result, an abnormal process can be easily specified.

Embodiment 5

As described in Embodiment 4, when an adjustment parameter of anabnormal process or a manufacturing apparatus relating to the abnormalprocess can be acquired from image data or characteristics (for example,brightness information) extracted from the image data, the manufacturingcondition can be rapidly adjusted. In the present embodiment, a systemthat specifies an adjustment parameter of an abnormal process or amanufacturing apparatus relating to the abnormal process by inputtingimage data or characteristics extracted from the image data will bedescribed.

FIG. 15 is a diagram showing an example of the system that estimates theabnormal process or the like. FIG. 15 is a functional block diagram. Acomputer system 1501 shown in FIG. 15 is a machine learning system,includes one or more processors, and is configured to execute one ormore arithmetic modules stored in a predetermined storage medium. Inaddition, an estimation process described below may be performed usingan AI accelerator. The computer system 1501 shown in FIG. 15 includes aninput unit 1503 to which the teacher data provided for learning or datarequired for the estimation process is input from a storage medium 1502or an input device 1503.

A learning device 1504 built in the computer system 1501 receives, asthe teacher data, a combination of at least one of image data input fromthe input unit 1503 and a characteristic of an image extracted from animage processing apparatus (not shown), a beam irradiation condition(inspection condition) of the charged particle beam apparatus, andinformation (sample information) regarding a type of a sample and anelement formed on the sample. Further, the learning device 1504 alsoreceives process abnormality information. Examples of the processabnormality information include a process that was determined as adefect in the past and was fed back to a manufacturing apparatus tocorrect the defect or a parameter of the process that was fed back tothe manufacturing apparatus. This information is stored in apredetermined storage medium as a data set in order to make thisinformation function as teacher data to be learned by the learningdevice.

The characteristic of the image is, for example, brightness or acontrast of a specific pattern and can be obtained by extractingbrightness information of a pattern specified by pattern matching or thelike or a specific pattern segmented by semantic segmentation or thelike. As the learning device, for example, a neural network, aregression tree, or a Bayes identifier can be used.

In addition, the beam irradiation condition is a blocking time or anirradiation time of a pulsed beam. The learning device 1504 reads theinspection recipe from the charged particle beam apparatus or receivesan input from the input device 1505 to receive this data as a part ofthe teacher data.

The learning device 1504 executes machine learning using the receivedteacher data. A learning model storage unit 1506 stores a learning modelthat is constructed by the learning device 1504. The learning modelconstructed by the learning device 1504 is transmitted to an abnormalprocess estimation unit 1507 and is used for estimating the abnormalprocess.

In the abnormal process estimation unit 1507, based on the learningmodel constructed by the learning device 1504, the abnormal process or aparameter to be fed back is estimated from the input image data or thecharacteristics extracted from the image data, and the input sample andinspection information.

By performing the estimation using the learning model that is learned asdescribed above, the manufacturing apparatus can be rapidly adjusted.

Embodiment 6

FIG. 16 is a diagram showing another system for deriving electricalcharacteristics of a sample. FIG. 17 is a top view of a sample on whicha DRAM that is one type of a semiconductor element to be inspected isformed. The DRAM is an element that charges a capacitor (storage node)using a voltage applied to a bit line 1703 by increasing a voltageapplied to a word line 1702 and applying a gate voltage to a transistor.Here, in an image shown in FIG. 17 , the description will be madeassuming that a word line contact 1701 (WLC) and a storage node contact1705 (SNC) are seen and a portion indicated by a dotted line such as adiffusion layer 1704 is not seen.

In the present embodiment, an example of evaluating the durability(reliability) of the DRAM by applying stress to the transistor multipletimes through the word line contact 1701 will be described. FIG. 18 is aflowchart showing a DRAM reliability evaluation process.

First, a sample moves to coordinates registered in the recipe, andimages are acquired so as to include both WLC and SNC (Steps 601 and602). Using the images acquired in Step 602, the positions of the WLC(first terminal) and the SNC (second terminal) are specified, and thenthe WLC is irradiated with a beam for stress application (Step 1801). Inthe present embodiment, the example of using a beam emitted from theelectron source of the scanning electron microscope as the beam forstress application has been described. However, another electron sourcefor stress application or a light source that emits light for stressapplication may be provided in a sample chamber of the scanning electronmicroscope and stress may be applied by using such a beam source.

Next, the SNC is irradiated with abeam for image acquisition to acquireimages (Step 1802). By repeating the stress application and the imageacquisition, a S curve is generated as shown in No. 1 in FIG. 19 (Step1803). FIG. 19 is a diagram showing an example of a GUI screen throughwhich a reliability determination result of a semiconductor element isdisplayed as an inspection result. When the voltage applied to the gatethrough the WLC exceeds a threshold, the gate is opened, and thus theSNC becomes bright. On the other hand, when characteristics deterioratedue to a hot carrier effect, the voltage applied to the gate effectivelydecreases to the threshold or lower, the gate is closed, and thus theSNC becomes dark.

A threshold for evaluating the reliability of an element is set from thenumber of times of stress application and a change in a parameter(brightness), and whether or not the characteristics deteriorate (thecharacteristics exceed or fall below the threshold) before reaching areliability guarantee time (number of times) is determined. The computersystem 303 reads a threshold from a reliability database 1601 dependingon the type of a semiconductor element or an inspection condition, anddetermines whether or not the characteristics exceed (or fall below) thethreshold. When the characteristics exceed (or fall below) thethreshold, the computer system 303 determines that the element to beinspected is normal, and When the characteristics fall below (or exceed)the threshold, the computer system 303 determines that the element to beinspected is defective (Steps 1804, 1805, and 1806).

No. 2 in FIG. 19 shows an example in which a terminal that supposed tobe energized and typically looks bright is displayed dark because voidsin the terminal migrate due to an electromigration phenomenon caused bythe irradiation of the beam for stress application such that the contactis disconnected. In this way, by setting an appropriate threshold for aphenomenon inducing a defect and evaluating characteristics when apredetermined number of times or a predetermined amount of stressapplication is performed, the reliability of the semiconductor elementcan be evaluated.

Further, a defect type can be determined using a characteristic amountextracted from a relationship between the number of times of stressapplication and the brightness. For example, a hot carrier effect and anelectromigration phenomenon can be distinguished from each other using adifference between the shapes of the S curves shown in No. 1 and No. 2of FIG. 19 .

Embodiment 7

In the present embodiment, a system that specifies (classifies) a typeof a defect based on a combination of the brightness information of apattern and the dimension or shape information of the pattern will bedescribed. (a) of FIG. 20 is a cross-sectional view of a lower wiring2005 and four plugs connected to the lower wiring. (b) of FIG. 20 is atop view of the four plugs. Among the four plugs, plugs 2003 and 2004are dimension defects in which the dimensions of the patterns in a topview are less than those of the plugs 2001 and 2002. In addition theplugs 2002 and 2004 taper defects in which the tapers thereof are largerthan those of the plugs 2001 and 2003. When this sample is irradiatedwith a beam, the brightness of the plug is inversely proportional to theamount of charge in the plug. In addition, the amount of charge in theplug is inversely proportional to a junction area between the plug andthe lower wiring. Further, the junction area between the plug and thelower wiring is proportional to the pattern dimension of the uppermostsurface and is inversely proportional to the taper. As a result, thebrightness of the plug is proportional to the pattern dimension in a topview and is inversely proportional to the taper. For example, among thefour plugs of FIG. 20 , the plug 2001 having a large pattern dimensionin a top view and a small taper angle has the highest brightness, theplug 2002 having a large pattern dimension in a top view and a largetaper angle and the plug 2003 having a small pattern dimension in a topview and a small taper angle have the second highest brightness, and theplug 2004 having a small pattern dimension in a top view and a largetaper angle has the lowest brightness. Accordingly, the dimensiondefect, the taper defect, and the composite defect of the dimension andtaper can be classified based on the combination of the brightnessinformation of the pattern of the uppermost surface and the dimensioninformation.

FIG. 21 is a diagram showing an example of the system that classifies atype of a defect based on the brightness information of the pattern andthe dimension or shape information of the pattern. The computer system303 is communicably connected to a design data storage medium 2101 thatstores design data (layout data) of a semiconductor device. A patternshape evaluation application 2102 stored in the memory 306 compares, forexample, the layout data read from the design data storage medium 2101and a pattern included in an actual image to each other and calculatesshape information (a pattern size, a dimension, a ratio of the size tothe layout data, or a magnitude relationship with the layout data).

A defect classification application 2103 specifies a defect type byreferring to a database storing the combination of the shape informationof the pattern and the brightness information and the type of the defectin association with each other. For example, as shown in FIG. 20 , theplugs 2002 and 2003 have the same brightness and different patterndimensions in a top view. Therefore, the plug 2002 is specified as ataper defect and the plug 2003 is specified as a dimension defect.

By referring to not only the brightness but also other characteristicssuch as a dimension or a shape, the number of categories of defectclassification can be increased.

Embodiment 8

As described using FIG. 1 , unique brightness information derived from ascan direction or an irradiation order of the beam with respect to aplurality of patterns can be obtained depending on types of defects. Asshown in FIG. 1 , when beam scanning is performed from one direction,the open defect or the like of the gate contact can be specified.However, in the case of the junction leakage defect of the drain, simplyby scanning from the left side to the right side, it is difficult todetermine whether the reason why the drain contact becomes brighter isthat the gate is opened by irradiation of the gate with a beam or thatcharge is not accumulated due to leakage.

In the present embodiment, as shown in FIG. 22 , a system or the likethat specifies a type of a defect by performing beam scanning in aplurality of directions (in the present embodiment, both directions)instead of beam scanning in one direction and referring to, for acombination of brightness of a plurality of patterns, a database storingrelated information between the combination of the brightness and typesof defects will be described.

As shown in FIG. 22 , by performing scanning along the scanningtrajectory 111 (moving an irradiation point in a first direction tosequentially irradiate a plurality of patterns with a beam) andperforming scanning along a scanning trajectory 2201 (moving anirradiation point in a second direction to sequentially irradiate aplurality of patterns with a beam), for example, when junction leakageoccurs in the drain, the drain contact 110 becomes brighter due to theleakage although the gate contact 109 is not yet irradiated with a beam.Here, it is desirable to perform the scanning along the scanningtrajectory 2201 after relaxing charge generated in the sample due to thescanning along the scanning trajectory 111.

The computer system 303 specifies a type of a defect by storing adatabase in advance which stores association between a combination ofbrightness information during beam scanning on plurality of patterns ina plurality of directions and types of defects in advance and referringto the database for a combination of brightness information extractedfrom an actual image that is acquired by beam scanning in a plurality ofdirections. In this way, by performing beam scanning in a plurality ofdirections, a type of a defect that cannot be specified by scanning inone direction can also be specified.

REFERENCE SIGNS LIST

-   -   1: electron beam source    -   2: condenser lens    -   3: diaphragm    -   4: pulsed electron generator    -   5: deflector    -   6: objective lens    -   7: sample electric field controller    -   8: detector    -   9: output adjustment circuit    -   10: sample stage    -   11: sample    -   21: acceleration voltage controller    -   22: irradiation current controller    -   23: pulse irradiation controller    -   24: deflection controller    -   25: focusing controller    -   26: sample electric field controller    -   27: stage position controller    -   28: control transmitter    -   31: detection signal processing unit    -   32: detection signal analysis unit    -   33: image or electrical characteristic display unit    -   34: database    -   41: operation interface

The invention claimed is:
 1. A system that is configured to becommunicable with an image acquisition tool and detects a defect of anelectric circuit formed on a semiconductor wafer from image dataacquired from the image acquisition tool or characteristics extractedfrom the image data, the system comprising: a computer system; and anarithmetic module that is executed by the computer system, wherein thecomputer system receives, from the image acquisition tool, image dataobtained by sequentially irradiating a plurality of contacts included ina transistor provided on the semiconductor wafer with a beam andextracts characteristics of the plurality of contacts sequentiallyirradiated with the beam from the received image data, thecharacteristics being included in the image data, or receivescharacteristics of the plurality of contacts sequentially irradiatedwith the beam from the image acquisition tool, the characteristics beingextracted from the image data, and derives a type of a defect byreferring to related information for the characteristics of theplurality of contacts, the related information storing thecharacteristics of the plurality of contacts, types of defects inassociation with each other, and an order in which the plurality ofcontacts were sequentially irradiated, wherein the plurality of contactsincludes two or more from a source contact, a gate contact and a draincontact.
 2. The system according to claim 1, wherein the characteristicsof the plurality of contacts are obtained when the plurality of contactsare irradiated with the beam at different timings.
 3. The systemaccording to claim 1, wherein the characteristics of the plurality ofcontacts are obtained when a beam irradiation point of the imageacquisition tool is moved in a plurality of directions relative to theplurality of contacts.
 4. The system according to claim 1, wherein therelated information is a database storing a plurality of characteristicsand types of defects in association with each other, the plurality ofcharacteristics being obtained by sequentially irradiating the pluralityof contacts included in a transistor with the beam.
 5. A non-transitorycomputer-readable medium storing a program that is configured toinstruct a processor to receive image data from the image acquisitiontool obtained by sequentially irradiating a plurality of contactsincluded in a transistor provided on the semiconductor wafer with a beamand to extract characteristics of the plurality of contacts sequentiallyirradiated with the beam from the received image data, thecharacteristics being included in the image data, or to receivecharacteristics of the plurality of contacts sequentially irradiatedwith the beam from the image acquisition tool, the characteristics beingextracted from the image data, and to derive a type of a defect byreferring to related information for the characteristics of theplurality of contacts, the related information storing thecharacteristics of the plurality of contacts, types of defects inassociation with each other, and an order in which the plurality ofcontacts were sequentially irradiated, wherein the plurality of contactsincludes two or more from a source contact, a gate contact and a draincontact.
 6. A system that detects a defect of an electric circuit formedon a semiconductor wafer from a netlist including electricalcharacteristics of a circuit element and connection information betweenterminals and image data acquired from an image acquisition tool orcharacteristics extracted from the image data, the system beingconfigured to be communicable with the image acquisition tool, thesystem comprising: a computer system; and an arithmetic module that isexecuted by the computer system, wherein the computer system receivesimage data obtained by sequentially irradiating a plurality of contactsincluded in a transistor provided on the semiconductor wafer with a beamfrom the image acquisition tool and extracts characteristics of theplurality of contacts from the received image data, the characteristicsbeing included in the image data, or receives characteristics of theplurality of contacts from the image acquisition tool, thecharacteristics being extracted from the image data, receives one ormore netlists, including the electrical characteristics of the circuitelement and the connection information between the terminals, in which arelationship between an equivalent circuit of an electric circuit formedon the semiconductor wafer and defect information is described from anetlist database, estimates characteristics of the plurality of contactsfrom one or more netlists or estimates netlists based on characteristicsof a plurality of contacts included in the image data, compares thecharacteristics of the plurality of contacts estimated from the netlistsand the characteristics of the plurality of contacts extracted from theimage data to each other or compares the netlists received from thenetlist database and the netlists estimated based on the characteristicsof the plurality of contacts included in the image data to each other,and outputs defect information described in a netlist selected based onthe comparison.
 7. The system according to claim 6, wherein the computersystem receives a netlist of an equivalent circuit of a normal electriccircuit and a netlist of an equivalent circuit of an electric circuitincluding a defect from the netlist database, compares the netlist ofthe equivalent circuit of the normal electric circuit and the netlist ofthe equivalent circuit of the electric circuit including the defect orcharacteristics of a plurality of patterns extracted from the netliststo netlists estimated based on characteristics of a plurality ofpatterns included in the image data or to characteristics of theplurality of patterns extracted from the image data, and determineswhether an electric circuit formed on the semiconductor wafer is anormal electric circuit or an electric circuit including a defect basedon the comparison.
 8. The system according to claim 6, wherein thecomputer system compares characteristics under each of a plurality ofimage acquisition conditions relating to a plurality of patternsacquired from the image acquisition tool under the plurality of imageacquisition conditions to characteristics extracted from the one or morenetlists, and outputs defect information described in a netlist selectedbased on the comparison.
 9. The system according to claim 6, wherein thecomputer system determines a manufacturing process that brings about thedefect based on a comparison of a netlist received from a netlistdatabase storing one or more netlists for each of manufacturingprocesses of the semiconductor wafer or characteristics of a pluralityof patterns extracted from the netlist to a netlist estimated based oncharacteristics of a plurality of patterns included in the image data orcharacteristics of a plurality of patterns included in the image data.10. A non-transitory computer-readable medium storing a program that isconfigured to instruct a processor to detect a defect of an electriccircuit formed on a semiconductor wafer from a netlist includingelectrical characteristics of a circuit element and connectioninformation between terminals, wherein the program is configured toinstruct a processor to receive an image data obtained by sequentiallyirradiating a plurality of contacts included in a transistor provided ona semiconductor wafer with a beam from an image acquisition tool and toextract characteristics of a plurality of contacts included in thereceived image data from the image data, or to receive characteristicsof a plurality of contacts extracted from the image data, to receive oneor more netlists, including the electrical characteristics of thecircuit element and the connection information between the terminals, inwhich a relationship between an equivalent circuit of an electriccircuit formed on the semiconductor wafer and defect information isdescribed from a netlist database, to estimate characteristics of theplurality of contacts from one or more netlists or estimate netlistsbased on characteristics of a plurality of contacts included in theimage data, to compare the characteristics of the plurality of contactsestimated from the netlists and the characteristics of the plurality ofcontacts extracted from the image data to each other or compares thenetlists received from the netlist database and the netlists estimatedbased on the characteristics of the plurality of contacts included inthe image data to each other, and to output defect information describedin a netlist selected based on the comparison.
 11. The system accordingto claim 1, wherein, by charge being accumulated in the gate contact,the gate of the transistor is opened or the source and the drain of thetransistor are electrically connected.
 12. The system according to claim1, wherein image data is data obtained by beam scanning of an imageacquisition tool such that the plurality of contacts are included in afield of view.
 13. The system according to claim 12, wherein image datais data obtained by beam scanning of the image acquisition tool in anarrangement direction of the plurality of contacts according to thearrangement order.
 14. The system according to claim 12, wherein imagedata is data obtained by beam scanning of the image acquisition tool forthe plurality of contacts in a first direction sequentially and by beamscanning of the image acquisition tool for the plurality of contacts ina second direction sequentially.
 15. The system according to claim 1,wherein the image data is a voltage contrast image data.
 16. The systemaccording to claim 6, wherein the defect information is determined basedon an order in which the plurality of contacts were sequentiallyirradiated.
 17. The non-transitory computer-readable medium according toclaim 10, wherein the defect information is determined based on an orderin which the plurality of contacts were sequentially irradiated.
 18. Thesystem according to claim 6, wherein the defect information isdetermined based on a rate of concordance between images in the imagedata or between the netlists.
 19. The non-transitory computer-readablemedium according to claim 10, wherein the defect information isdetermined based on a rate of concordance between images in the imagedata or between the netlists.